DESIGNING AND EVALUATING A CONTEXTUAL MOBILE LEARNING APPLICATION TO SUPPORT SITUATED LEARNING
ABEER ALNUAIM
A thesis submitted in partial fulfilment of the requirements of the University of the West of England, Bristol for the degree of Doctor of Philosophy
Faculty of Environment and Technology, University of the West of England, Bristol
Abstract
This research emerged from seeking to identify ways of getting Human-Computer Interaction Design students into real world environments, similar to those in which they will eventually be designing, thus maximising their ability to identify opportunities for innovation. In helping students learn how to become proficient and innovative designers and developers, it is crucial that their ‘out of the classroom’ experience of the environments in which their designs will be used, augments and extends in-class learning. The aim of this research is to investigate firstly, a blended learning model for students in higher education using mobile technology for situated learning and, secondly, the process of designing a mobile learning app within this blended learning model. This app was designed, by the author, to support students in a design task and to develop their independent learning and critical thinking skills, as part of their Human-Computer Interaction coursework. The first stage in designing the system was to conduct a comprehensive contextual inquiry to understand specific student and staff needs in the envisaged scenario.
In addition, this research explores the challenges in implementing and deploying such an app in the learning context. A number of evaluations were conducted to assess the design, usability and effectiveness of the app, which we have called sLearn. The results show an improvement in scores and quality of assessed work completed with the support of the sLearn app and a positive response from students regarding its usability and pedagogic utility. The promising results show that the app has helped students in developing critical thinking and independent learning skills. The research also considers
in a higher education setting. There were issues discovered in regards to the context of use such as usability of interface elements and feeling self-conscious in using the app in a public place.
The model was tested with two other student cohorts: User Experience and Engineering students, to further investigate best practice in deploying mobile learning in higher education and examine the suitability of this learning model for different disciplines. These trials suggest that the model is indeed suitable and, the engineering study in particular has demonstrated that it has the potential to support the learning in-situ of students from non-computing disciplines.
Table of Contents
1 Chapter One: Introduction ... 13
1.1 A contextual mobile learning model ... 14
1.1.1 Scope of the study ... 17
1.1.2 Aims, Objectives and Research Questions ... 18
1.2 Research Contributions ... 19
1.3 Thesis Structure ... 20
1.4 Publications ... 21
2 Chapter Two: Mobile Learning and Pedagogy ... 23
2.1 Learners and Technology ... 23
2.2 A Debate on Definition ... 25
2.3 Drivers Behind Mobile Learning ... 28
2.4 Pedagogical Aspects in Mobile Learning ... 30
2.4.1 Situated learning ... 32
2.4.2 Context-‐aware and location-‐based learning ... 33
2.4.3 Inquiry-‐based learning and Problem based learning ... 35
2.4.4 Collaborative learning ... 37
2.4.5 Lifelong and Informal learning ... 38
2.5 HCI Teaching ... 40
2.5.1 Uses of technology in HCI teaching ... 42
2.6 Critical Thinking and Reflection ... 43
2.6.1 Definition ... 43
2.6.2 Critical thinking skills ... 44
2.6.3 Reflection ... 44
2.6.4 Assessment of critical thinking and reflection ... 46
2.8 Conclusion ... 48
3 Chapter Three: Designing Mobile Learning ... 50
3.1 Mobile Learning Challenges ... 50
3.1.1 Technological Challenges ... 51
3.1.2 Educational Challenges ... 51
3.1.3 Ethical Challenges ... 53
3.1.4 Design Challenges ... 54
3.1.5 Evaluation Challenges ... 55
3.2 Contexts for Mobile Learning ... 56
3.2.1 Requirements frameworks for designing mobile learning ... 58
3.3 Evaluating Mobile Applications ... 64
3.4 Usability ... 68
3.5 Evaluation and Usability Methods ... 70
3.5.1 Inspection Methods ... 70 3.5.2 Test Methods ... 71 3.6 User Experience ... 72 3.7 Evaluations in-‐Situ ... 73 3.7.1 Physical Context ... 74 3.7.2 Social Context ... 74 3.8 Pedagogical Evaluation ... 75 3.9 Operational concepts ... 76 3.10 Conclusion ... 77
4 Chapter Four: Development of a contextual mobile learning Model ... 79
4.1 Phase One: Requirements and Contextual inquiry ... 83
4.1.1 Interviews ... 84
4.1.3 Survey of Mobile ownership ... 89
4.1.4 Previous Submitted Coursework ... 94
4.1.5 Focus Group ... 97
4.1.6 Usability review of mobile applications ... 97
4.1.7 Phase One Findings ... 100
4.2 Phase Two: Theoretical Framework Development ... 101
4.3 Conclusion ... 105
5 Chapter Five: The Design and Evaluation of a contextual situated mobile learning app (sLearn) ... 107
5.1 Defining Requirements ... 108
5.1.1 Scenario of use of the app ... 109
5.1.2 Functional and Non-‐Functional Requirements ... 111
5.1.3 System Architecture ... 113
5.2 Prototype Design and Evaluation Iterations ... 114
5.2.1 Stage One ... 115
5.2.2 Stage Two ... 121
5.3 Conclusion ... 132
6 Chapter Six: Testing the contextual mobile learning model ... 133
6.1 Deployment One: HCI Students ... 135
6.1.1 Assignment specification ... 135
6.1.2 Evaluation Design ... 138
6.1.3 Participant and deployment details ... 141
6.2 In-‐Context Evaluation ... 143
6.2.1 Participants and Evaluation Design ... 144
6.3 Deployment Two: User Experience (UX) Students ... 146
6.4 Deployment Three:Engineering Students ... 150
6.4.1 Contextual Inquriy ... 151
6.4.2 Customising sLearn’s content ... 152
6.4.3 Deploying sLearn in the Engineering Context ... 153
6.5 Methods of Analysis ... 155
6.5.1 Qualitative data ... 155
6.5.2 Quantitative data ... 156
6.5.3 Research Validity ... 157
6.6 Conclusion ... 159
7 Chapter Seven: Results and Analysis ... 160
7.1 Deployment One: HCI Results ... 160
7.1.1 In-‐class group presentations – Assessing learners’ analysis and critical thinking skills ... 160
7.1.2 In-‐depth content analysis of students’ work ... 174
7.1.3 Questionnaire – Assessing Interface and Pedagogic Usability ... 177
7.1.4 Discussion ... 181 7.2 In-‐Context Evaluation ... 184 7.2.1 Observations Results ... 184 7.2.2 Interviews ... 186 7.2.3 Questionnaire ... 187 7.2.4 Discussion ... 188
7.3 sLearn Iteration Six ... 191
7.3.1 Redesgin ... 191
7.3.2 Clearer Instructions ... 192
7.4 Deployment Two: UX Results ... 193
7.4.1 Observations of usage ... 194
7.4.3 Submitted Coursework ... 198
7.4.4 Discussion ... 200
7.4.5 Comparison between HCI and UX deployments ... 201
7.4.6 Reliability of questionnaires ... 203
7.4.7 Level of Andriod expertise ... 204
7.5 Deployment Three: Engineering Results ... 206
7.5.1 Deployment Results ... 206
7.5.2 Discussion ... 208
7.6 Discussion of all evaluations conducted ... 209
7.6.1 Design and GUI ... 210
7.6.2 Usability, User Experience and Students’ Perspective ... 211
7.6.3 Blended Learning Model ... 213
7.7 Guidelines for implementing a mobile application for situated learning activities in HE ... 218
7.8 Conclusion ... 220
8 Chapter Eight: Conclusions and Future Work ... 223
8.1 Evaluation of research ... 223
8.1.1 Objective 1 ... 223 8.1.2 Objective 2 ... 224 8.1.3 Objective 3: ... 226 8.1.4 Objective 4: ... 227 8.2 Research Contributions ... 228 8.3 Limitations ... 230 8.4 Future Work ... 231 9 References ... 233
List of Figures
FIGURE 1 BLENDED LEARNING MODEL 15 FIGURE 2 INTERDISCIPLINARY SCOPE OF THIS RESEARCH 17 FIGURE 3 INPUT/OUTPUT MODEL OF REFLECTION (SOURCE: MOON, 2001, P.5) 46 FIGURE 4 THE CONTEXT OF MOBILE INTERACTION (SOURCE: SAVIO AND BRAITERMAN, 2007,
P.2) 57
FIGURE 5 A FRAMEWORK FOR M-‐LEARNING DESIGN REQUIREMENTS (SOURCE: RYU AND
PARSONS, 2008, P.12) 60
FIGURE 6 DESIGN FRAMEWORK FOR MOBILE LEARNING (SOURCE:LIU ET AL., 2008, P.185) 62 FIGURE 7 THREE LEVEL EVALUATION FRAMEWORK (SOURCE: VAVOULA AND SHARPLES,
2009) 67
FIGURE 8 ITERATIVE DEVELOPMENT PROCESS 80 FIGURE 9 DETAILED ACTIVITIES WITHIN THE ITERATIVE DEVELOPMENT PROCESS 81 FIGURE 10 DEVELOPMENT TIMELINE SHOWING THE DIFFERENT ACTIVITIES THAT INVOLVED
THE STAKEHOLDERS 82
FIGURE 11 REQUIREMENTS AND CONTEXTUAL INQUIRY MIXED METHODS 83
FIGURE 12 DAILY WEB SURFING 92
FIGURE 13 PERCENTAGES OF THE OCCURRENCES OF ISSUES 97 FIGURE 14 SLEARN'S ACTIVITY DESIGN FRAMEWORK 103 FIGURE15:HIERARCHICAL TASK DIAGRAM FOR USING THE APP 110
FIGURE 16: SLEARN’S FLOWCHART 111
FIGURE 17 SYSTEM ARCHITECTURE 114
FIGURE 18: ITERATION ONE 116
FIGURE 19: ITERATION TWO 117
FIGURE 20 ITERATION THREE 119
FIGURE 21 STAGE ONE ITERATIONS STAGE TWO 120 FIGURE 22: LOCATION’S SCREEN OF ITERATION FOUR 126
FIGURE 24 STAGE TWO ITERATIONS 131
FIGURE 25 TESTING TIMELINE 134
FIGURE 26 CONTEXTUAL BLENDED LEARNING MODEL FOR THE HCI MODULE 138 FIGURE 27 HCI’S DEPLOYMENT METHODOLOGY 142 FIGURE 28 HCI’S EVALUATION METHODS 143 FIGURE 29 DUE'S EVALUATION METHODS 146 FIGURE 30 CONTEXTUAL BLENDED LEARNING MODEL FOR THE UX MODULE 148 FIGURE 31 UX’S EVALUATION METHODOLOGY 150 FIGURE 32 GROUP B'S PACT PART 1 166 FIGURE 33 GROUP B'S PACT PART 2 167 FIGURE 34 GROUP B'S PACT PART 3 168
FIGURE 35 GROUP C'S PACT 168
FIGURE 36 GROUP L'S PACT 169
FIGURE 37 GROUP G'S PACT 169
FIGURE 38 GROUP J'S PACT 170
FIGURE 39 GROUP J'S PACT PART 2 170 FIGURE 40 GROUP A'S REQUIREMENTS 172 FIGURE 41 GROUP F'S REQUIREMENTS 172 FIGURE 42 GROUP H'S REQUIREMENTS 173 FIGURE 43 GROUP M'S REQUIREMENTS 174 FIGURE 44 GROUP M'S REQUIREMENTS PART 2 174
FIGURE 45 HCI’S SUS SCORES 178
FIGURE 46 A STUDENT OBSERVING THE ENTRANCE AND THE FOOD AREA OF THE CAFETERIA
186
FIGURE 47 DUE’S SUS SCORES 188
FIGURE 48 MORE TEXTBOXES ADDED TO EACH LOCATION 192 FIGURE 49 CLEARER INSTRUCTION ON WHAT TO DO IN EACH LOCATION 193 FIGURE 50 UX STUDENTS INTERACTING WITH SLEARN 195 FIGURE 51 UX STUDENTS INTERACTING WITH SLEARN ON THEIR TABLET 196
FIGURE 53 ENGINEERING’S INDIVIDUAL SUS SCORES 207 FIGURE 54 CATEGORISING FINDINGS 210
List of Tables
TABLE 1 AN ACTIVITY-‐BASED CATEGORISATION OF MOBILE TECHNOLOGIES AND LEARNING
(NAISMITH ET AL., 2004) 31
TABLE 2 TYPES OF FORMAL AND INFORMAL LEARNING (SO ET AL., 2008) 38 TABLE 3 PEDAGOGICAL USABILITY METRICS ADAPTED FROM IVANC ET AL. (2012) 75
TABLE 4 OPERATING SYSTEMS 91
TABLE 5 MEAN RANKS FOR (GENDER) 94 TABLE 6 ISSUES AND OCCURRENCES 95 TABLE 7 ANALYSIS OF SITUATED LEARNING ACTIVITY USING SLEARN 104 TABLE 8: FUNCTIONAL REQUIREMENTS 112 TABLE 9: NON-‐FUNCTIONAL REQUIREMENTS 113 TABLE 10 HCI’S EVALUATION METHODOLOGIES 139 TABLE 11 PEDAGOGIC USABILITY QUESTION RESULTS 141 TABLE 12 IN-‐CONTEXT EVALUATION METHODOLOGIES 145 TABLE 13 EVALUATION DESIGN FOR UX 149 TABLE 14 PEDAGOGICAL USABILITY STATEMENTS 149 TABLE 15 EVALUATION DESIGN FOR ENGINEERING 155 TABLE 16 HCI STUDENTS’ COURSEWORK ALLOCATED MARKS-‐ SLEARN USED 161 TABLE 17 HCI’S COURSEWORK ALLOCATED MARKS-‐ SLEARN NOT USED 162 TABLE 18 CONTENT ANALYSIS OF STUDENTS' WORK (THE CONTEXT) 175 TABLE 19 CONTENT ANALYSIS OF STUDENTS' WORK (THE PEOPLE AND ACTIVITIES) 175 TABLE 20 CONTENT ANALYSIS OF STUDENTS' WORK (TECHNOLOGY) 176 TABLE 21 HCI’S PEDAGOGIC USABILITY QUESTION RESULTS 179 TABLE 22 IN-‐CONTEXT OBSERVATION ISSUES 184 TABLE 23 UX’S PEDAGOGICAL USABILITY RESULTS 197
TABLE 24 UX'S COURSEWORK ANALYSIS 199 TABLE 25 A COMPARISON BETWEEN HCI AND UX 202 TABLE 26 HCI'S QUESTIONNAIRE RELIABILITY TEST 203 TABLE 27 UX QUESTIONNAIRE RELIABILITY TEST 203
TABLE 28 LEVEL OF EXPERTISE 204
TABLE 29 STUDENTS' POSITIVE RESPONSES PERCENTAGES 205 TABLE 30 ENGINEERING’S PEDAGOGICAL USABILITY 207 TABLE 31 GUIDELINES FOR DESIGNING A MOBILE APP FOR IN-‐SITU ACTIVITIES IN HE 219
Acronym List
DUE Designing the User Experience
GPS Global Positioning System
GUI Graphical user interface
HCI Human-Computer Interaction
UCD User-Centred Design
HE Higher Education
HOTS Higher Order Thinking Skills
ID Interaction Design
PACT People, Activities, Context, and Technology Framework
PDA Personal Digital Assistant
SUS System Usability Scale
UI User Interface
1 Chapter One: Introduction
In recent years, mobile learning has been growing as a significant research area encompassing educational technologies, mobile and wireless computing, and mobile Human-Computer Interaction. It is growing more and more in popularity with the advancement of mobile technologies and the widespread use of smartphones and tablet PCs and has been incorporated into many disciplines such as Science (Chu et al., 2010; de-Marcos et al., 2010; Jones et al., 2013), Computing (Hwang et al., 2010; Seraj and Wong, 2012), and Language Learning (Chen and Hsu, 2008; Guerrero et al., 2010) to name but a few. Research into mobile learning has evolved from a focus on primary and secondary education to include mobile learning in higher education (HE) in recent years. Researchers have been investigating various ways to enhance HE students’ learning experience, provide help to institutions in order to employ the new technologies (Kukulska-Hulme, 2012), understand students’ perspective (Marwan et al., 2013; Gikas and Grant, 2013; Khaddage and Knezek, 2013), and to investigate promoting higher order thinking skills through mobile learning (Norouzi et al., 2012; Cheong et al., 2012).
The idea for this research emerged from teachers of interaction design at the University of the West of England seeking more efficient and effective ways of exposing their students to real world environments, similar to those in which they will eventually be designing. Using the traditional model where students are sent out into real-world environments with a brief to be evaluative and analytical, without the presence of a teacher, can lead to a superficial and frustrating experience. This is especially true for students with beginning levels of analysis and limited critical thinking skills. It is not always possible for
teachers to accompany students and, moreover, it might not be beneficial for students to have immediate input from teachers, but rather to have prompts to provoke the development of their own thinking.
This thesis is thus driven by the desire to explore and exploit the opportunities offered by current mobile devices to help enrich the learning experience of HE students learning in real world environments.
The following sections start with an overview of the contextual mobile learning model used in this thesis. This overview also describes the initial concept, motivation and scope of this research, aims, objectives and research questions. Finally, the thesis structure is outlined and publications are listed.
1.1 A contextual mobile learning model
This thesis investigates the structure of a blended learning model (Littlejohn and Pegler, 2007) using mobile technology for students in higher education. Within this model the purpose of the mobile application is to provide students with contextual information to support learning in-situ where the learning context and location are taken into consideration. This contextual information prompts the students to explore various aspects of the immediate environment, supporting their understanding of the context (Parsons et al., 2007).
The thesis also investigates the process of designing this mobile learning app within the blended learning model. It is envisaged that careful consideration of the design of the mobile learning application and the content provided can be beneficial for augmenting students’ learning. This is supported by the work of Cook et al. (2008) among others who say that targeted learning hints from the lecturer and the ability to provide the learner with a collaboration facility can
‘…maintain a balance between effective support and intrusion’ and could bridge the gap between formal and informal learning (Cook et al., 2008, p.16-17).
The following figure shows the blended learning model developed in this research, of which the app is a part.
Figure 1 Blended learning model
The basis for developing the blended m-learning model was drawn from the lecturers’ experience and supported by the literature as follows:
• Students struggling to analyse real world environments and develop new ideas could be provided with the appropriate guidance from a mobile application. This is supported by the work of Cook et al. (2008) mentioned above.
• Mobile learning applications can provide contextual information that could help students stay focussed on the purpose and outcome of the activity, rather than being distracted by the process (Ryu and Parsons, 2008). Thus, this maximises their benefit from the real world experience while still implicitly developing an understanding of the process.
• Sharing comments, ideas and perhaps stories if desired, may enable students to benefit from their peers’ knowledge and different perspectives as known in the collaborative learning theory (Naismith et al., 2004). Incorporating technology to support collaborative learning was successful in promoting sharing and collaboration as will be shown in examples of research discussed in chapter two.
These findings relating to the benefits of a blended m-learning model inform this research in formulating a framework to develop a mobile app to be integrated into traditional teaching. The research itself explores further the effectiveness of the approach within the context of different student cohorts. These were students enrolled in the following modules: Human-Computer Interaction, User Experience, Designing the User Experience and students enrolled in two Engineering courses: Civil Engineering and River and Costal Engineering.
In order to provide the students with an enhanced and rich experience, this research is also interested in understanding the appropriate design, the usability and user experience issues for such mobile application. The initial situated learning activity was developed for undergraduates enrolled in the Human-Computer Interaction (HCI) module in the Department of Computer Science and Creative Technologies at the University of the West of England.
1.1.1 Scope of the study
This research contributes to the field of Human-Computer Interaction (HCI) and concerns the area of mobile learning and endeavours to improve learning
in-situ by providing contextual information to learners.
Figure 2 Interdisciplinary Scope of this research
As the figure above shows, the focus of thesis is at the intersection of the disciplines of mobile technology, design, and education. The challenges of designing and evaluating mobile applications for students in higher education are discussed in chapter three.
The intention was to bring together understanding of mobile technology, usability, user experience and pedagogy to form a well-designed m-learning model, adopting an interdisciplinary perspective. Pedagogical and usability studies have helped determine the learning content and the design and functionality of the app.
1.1.2 Aims, Objectives and Research Questions
The aims of this research are to investigate, firstly, a blended learning model for students in higher education using mobile technology for situated learning, and secondly, the process of designing a mobile learning app within this blended learning model.
To achieve these aims the following objectives have been identified:
1. To construct and demonstrate a model for a pedagogical activity assisted by a mobile learning app to facilitate independent study, and reflection and critical thinking in a more structured manner.
2. To carry out and review a user-centred iterative design process for developing the mobile app.
3. To review the user experience and usability of the contextual mobile application prototype.
4. To review students’ perceptions of the pedagogical usability provided by the mobile application.
The research questions are:
1. How effective is mobile learning in providing students with the necessary guidance in a situated learning activity without the physical
presence of a tutor/lecturer? Effectiveness will be considered in terms of improving ability for critical thinking and synthesis.
2. What are the pragmatic issues when deploying a mobile learning app in a blended learning environment?
3. What evaluation criteria and techniques can be used to evaluate such mobile learning apps?
1.2 Research Contributions
The outcome of this research lies in the novelty of the design and development of a contextual mobile learning model in HCI that can be applied to different disciplines. The model has been shown to be applicable to the teaching of the subjects of Human-Computer Interaction and User Experience. It has also been shown to be applicable to the teaching of Risk Assessment within Engineering, and theoretically, it can be applied to any discipline that requires its students to work in real world settings.
This research identifies and provides evidence of benefits of mobile learning: firstly, mobile learning can promote independent learning; secondly, that structured prompts delivered in-situ by means of an interactive app promotes critical thinking in understanding of context for design.
The research also presents further evidence regarding the benefits of contextual evaluations of mobile applications in discovering issues that tend to be missed in lab evaluations.
In addition, this research suggests guidelines for implementing a mobile application for situated learning activities in HE.
• What makes contextual mobile apps effective in teaching HCI students how to assess context in design.
• Challenges associated with mobile learning application evaluation.
1.3 Thesis Structure
This thesis consists of eight chapters. The first three chapters review the literature in mobile learning and designing mobile learning apps. The next three chapters present the methodology and analysis of the results. The concluding chapter provides discussions and future work. Below is a brief overview of the content of each chapter.
Chapter Two presents the literature on mobile learning. It looks at the
motivation for implementing mobile learning, the use of mobile devices in education and the pedagogical theories related to this research.
Chapter Three discusses the challenges faced when implementing mobile
learning, reviews the design requirements for mobile learning and investigates the literature on the evaluation of mobile learning and on usability both in general, and specifically for mobile learning.
Chapter Four discusses the development of the contextual mobile learning
app (sLearn) produced for this research. The development proceeded in four phases, following the User-Centred Design Process (UCD). This chapter explains the methodologies and work done for the first two phases of the development cycle: the requirements and contextual inquiry and the theoretical framework development.
Chapter Five discusses the last two phases of the development: the design
and prototyping of the sLearn mobile app and the evaluations and usability studies conducted as part of the iterative design approach.
Chapter Six explains the testing methodologies used in evaluating the
effectiveness of the framework. It explains in detail the methods used in all studies conducted as part of this thesis: the HCI, User Experience (UX), In-context evaluation, and Engineering.
Chapter Seven discusses the results and analysis of testing explained in
chapter six, it provides a categorised discussion of issues discovered from all the studies to answer the research questions, and delivers guidelines for implementing a mobile application for situated learning activities in HE.
Chapter Eight provides the conclusion, an evaluation of the research, a
statement of the research contribution and an identification of future work to be carried out.
1.4 Publications Journal:
A. Alnuaim A., Caleb-Solly, P. and Perry, C., (2014). Evaluating the effectiveness of a Mobile Location-based Intervention for Improving Human-Computer Interaction Students’ Understanding of Context for Design. International Journal of Mobile Human-Computer Interaction (IJMHCI). 6 (3), pp. 16-31.
Book:
location-requirements analysis study. In: Sampson, D.G., Ifenthaler, D., Spector, J.M. and Isaias, P., eds. (2014) Digital Systems for Open Access to Formal and Informal Learning. Springer. ISBN 978-3-319-02263-5
Conference:
C. Alnuaim A., Caleb-Solly, P. and Perry, C., 2012. Location-Based Mobile Learning for Higher Education Students – Developing an Application to Support Critical Thinking. In the Proceedings of the 11th World Conference on Mobile and Contextual Learning (mLearn12). Helsinki, Finland, October 16-18.
D. Alnuaim A., Caleb-Solly, P. and Perry, C., 2012. A Mobile Location-Based Situated Learning Framework for Supporting Critical Thinking – A Requirements Analysis Study. In the Proceedings of the IADIS International Conference Cognition and Exploratory Learning in Digital Age (CELDA 2012). Madrid, Spain, October 19-21, p. 163-170.
E. Alnuaim A., Caleb-Solly, P. and Perry, C., 2014, Enhancing Student Learning of Human-Computer Interaction using a Contextual Mobile Application. [In Preparation]
2 Chapter Two: Mobile Learning and Pedagogy
In the past two decades, education has been significantly affected by evolving technologies. Firstly Computer-based teaching and learning, then online and electronic learning (e-learning), and more recently mobile and ubiquitous learning (m- and u- learning). This has changed many activities undertaken by students and has enhanced their experience. Mobile learning is thought of in terms of the use of mobile device such as PDAs, smartphones, tablet PCs, and mobile phones. The mobility of these devices opened opportunities in education for both teachers and students/learners. It endorsed learning at anytime anywhere. Thus, it is not restricted to a particular physical space such as schools and universities. This motivated research on various activities that could be carried out with mobile devices in education to illustrate their benefits and observe their drawbacks.
In this chapter, a literature review of the current state of the art is surveyed. It starts with the debate on the digital natives, examines in greater detail various definitions of mobile learning, the motivation behind implementing it in education, and then considers pedagogical aspects of mobile learning.
2.1 Learners and Technology
Living in an era of advanced technologies, many engage with the new technologies available, leading to a new classification: Prensky (2001) has divided the population into ‘digital natives’ and ‘digital immigrants’. People born between 1980 and 1994 are immersed in technology in their everyday lives and are thus termed ‘digital natives’. However, those born prior to 1980 are ‘ digital immigrants’ who tend to have fewer previously learnt technological
Another related term the ‘millennial’ (Howe & Strauss, 2000) identifies particularly those who socially interact with their peers, wish to be connected, and prefer collaborative learning (Raines, 2002; Oblinger & Oblinger, 2005). This generation of students interacts and connects through Facebook, Twitter, mobile phones, and emails. This has led to a debate on whether firstly the ‘digital native’ generation exists and secondly on how educational institutions might consider the potential of adapting learning technologies to this generation’s advantage (Bennett et al., 2008).
Nagler and Ebner (2009, p.7) found that ‘digital natives’ or the ‘net generation’
“…exists if we think in terms of basic communication tools like e-mail or
instant messaging. Writing an email, participating in different chat rooms or contributing to a discussion forum is part of a student’s everyday life”. Kennedy et al. (2008) noted, however, that being in the net generation does not mean being able to use technology deliberately to enhance the learning experience at university.
These studies and more all came to similar conclusions, that being in the ‘digital native’ generation does not explain the context and ways in which technologies are being employed. Thus, in order to understand how and why ‘digital natives’ use the technology, more investigation is required. A more recent study conducted by Margaryan et al. (2011) came to the same conclusions. Students still prefer the “conventional, passive and linear forms of learning and teaching” (p.439). While Margaryan et al. (2011) agree that students’ experience using some technologies may exceed that of their lecturers in terms of time spent and direct face to face engagement, they argue that their awareness of the usage of technologies in learning is
restricted by their understanding of the “potential affordances and application of these tools and by their narrow expectations of learning in higher education. Students have limited understanding of what tools they could adopt and how to support their own learning” (p.439).
It is thus unwise to ask educational institutions to make a dramatic change in their teaching and learning methods relying on this generation’s daily use of technology. While some educational institutions may prefer to use traditional methods, others may need to make changes to accommodate new technologies. Bates et al. (2011) argue that implementing technology in teaching and learning is essential and educational institutions need to consider investing in technology.
According to Thomas (2005, p.1), “…pervasive learning is about using the technology that a learner has at hand to create relevant and meaningful learning situations, that a learner authors himself, in a location that the learner finds meaningful and relevant”. This suggests that technology has provided the learner with more opportunities for personalised and contextual learning. Such pervasive learning has influenced many researchers in educational technologies to further investigate m-learning. However, creating mobile learning applications should support and exploit students’ new ways of interacting and communicating. The next section discusses in detail the debate on the definition of mobile learning.
2.2 A Debate on Definition
Traxler (2007), were eager to show that m-learning is not a reduced version of e-learning (Belshaw, 2011). According to Traxler (2007, p.14), mobile technologies change the settings for the learning and the delivery method. This can be defined as “just-in-time, just-enough, and just-for-me”.
According to Winters (2007) there are four perspectives in which research applies to mobile learning:
1- Technocentric: where technology is their main concern and mobile learning means using mobile devices in learning such as using mobile phones, PDAs, tablet PCs in learning. For example, Sharples’ et al. (2002) and Traxler’s (2005) emphasised at first the mobility of the device as offering the defining features of mobile learning. However, emphasis soon shifted from the mobility of the device to that of the learner, as shown in point 2 below.
2- Relationship to learning: mobile learning here is an extension to e-learning that uses mobile devices. Traxler (2005) commented on this perspective and that the technocentric/e-learning definitions aim to show that mobile learning is a portable version of e-learning, which emphasises the technical issues.
3- Challenging formal education: mobile learning is seen in relation to traditional learning, perceived by some as taking over traditional classroom learning. Quinn (2011) provides an example of this, defining mobile learning as not “…putting e-learning courses on a phone…” Rather he suggests that: “…you should not think about mLearning as delivery of courses. mLearning is about augmenting our learning—and our performance. This includes a role in
formal learning and, occasionally can be the delivery mechanism for a full learning solution, but the real opportunity is augmenting learning and performance, not learning delivery” (Quinn, 2011, p.17). The idea that augmentation is fundamental to mobile learning was first argued by Metcalf (2006).
4- Learner-centred: this concentrates on the mobility of the individual learner, which takes advantage of the technologies. O’Malley et al. (2003, p.6) shifted their perception from the device to the leaner, defining it as “Any sort of learning that happens when the learner is not at a fixed, predetermined location, or learning that happens when the learner takes advantage of learning opportunities offered by mobile technologies” (O’Malley et al., 2003; Vavoula et al., 2004).
According to Belshaw (2011) the focus has shifted from the mobile technology to its use in aiding learning on the move. As, Woodill (2011, p.12) acknowledges that there is a shift in the perception of mobile learning, “Ten years ago, mobile learning was about displaying e-learning on a small screen”. He argues that it opens the horizon for learners to learn in ‘anywhere anytime’ manner and accessing information when needed. Walker (2007) emphasises that mobile learning is not only about the technology but also about the ability to learn in different contexts.
Other researchers attempt to provide a set of criteria to determine whether mobile learning is indeed mobile learning. For example, Lee and Lee (2008)
claim that it must be situated, learner-driven and spontaneous, customised, connected, and flexible.
The above discussion of how m-learning is perceived, shows how its definition can dramatically gain new dimensions as the technology advances. In terms of Winter’s (2007) classification, this research might be considered as learner-centred, challenging formal education. Moreover, Lee and Lee’s (2008) criterion-based definition seems to be in line with the purpose of this research emphasizing a number of characteristics that shape mobile learning. Traxler’s definition argues that mobile learning can provide learners with the opportunity to participate in an augmented activity on the move. These characteristics were taken into consideration in developing the framework at the centre of this study discussed in 4.2.
2.3 Drivers Behind Mobile Learning
Many argue for the significance of mobile technologies in learning per se, while others argue that learners are motivated to use mobile technologies in learning for a number of factors discussed below (Jones et al., 2007).
According to Jones et al. (2007) and Jones et al. (2006) there are six motivating factors behind the use of mobile devices in learning: Control, ownership and appropriation, fun, communication, learning-in-context, and continuity between contexts.
Jones et al. (2006) argue that experienced mobile users will have a high level of motivation to use different settings of the device to acquire knowledge and extend their learning activities. In addition, using mobile devices motivates informal learning in which leaners might change tasks to suit different contexts (Jones et al., 2006). Furthermore, mobile learning can enhance and enrich the
outdoor learning experience. According to Dillon et al. (2006, p. 107) research has shown that learning outdoors can help learners develop their knowledge and add meaningful and valuable experience if the activity was “…properly conceived, adequately planned, well taught and effectively followed up”.
Researchers, such as Kukulska-Hulme and Traxler (2005), Rogers et al. (2005), and Ryu and Parsons (2008), argue that the significance of mobile learning lies in the learner’s ability to be immersed in situations in which learning really arises.
Ryu and Parsons (2008) argue that mobile learning can successfully integrate with and aid student’s learning experience allowing students to benefit significantly from any contextual help provided. Kukulska-Hulme (2010) argues that mobile learning helps learners in fulfilling their personal needs. Learners are motivated by the very fact that they are using their own mobile devices.
Others encourage the use of mobile learning not only for the delivery of learning material, but also for the promotion of collaborative learning, administration of assessment, and supplementation of support and knowledge (Brown and Metcalf, 2008). Quinn (2011) defines four areas in which mobile devices can contribute to learning, Quinn’s four C’s of mobile learning are: capturing information, accessing content in the form of media, communicating with others, and the ability to compute responses.
Furthermore, Elias (2011) argues that mobile learning opens a number of opportunities to learners:
• Although the cost is generally an issue for some, mobile devices can be cheaper than many desktops and laptops. However, accessing the network may still be problematic issue.
• The possibility of accessing and creating multimedia.
• The possibility of continuous learning support.
The factors discussed above which motivate the implementation of mobile learning all apply to this research, namely: the opportunities afforded for learning in context, communication and collaboration, accessing content in the form of media, continuous learning support, control, contextual help for students, and capturing information. Having identified benefits of mobile learning that are relevant to this study, the next section discusses the pedagogical theories in mobile learning related to research of this thesis.
2.4 Pedagogical Aspects in Mobile Learning
Taylor et al. (2006) claimed that many pedagogical theories failed to capture the distinctive character of mobile learning. This was due to the lack of expansion to accommodate learning outside the classroom environment, which is personally regulated and motivated. The concentration was on learning through a teacher in the classroom environment.
However, learning theories can be applied to mobile technologies to add a different dimension to the experiences. Naismith et al. (2004) looked at various learning theories in which mobile technologies could be used to create theoretical based mobile learning. They have identified six theories: Behaviourist, Constructive, Situated, lifelong and informal, collaborative, and learning and teaching support.
Table 1 An Activity-based categorisation of mobile technologies and learning (Naismith et al., 2004)
Themes Key Theorist Activities
Behaviourist learning Skinner, Pavlov • Drill and feedback
• Classroom response systems
Constructive learning Piaget, Bruner, Papert Participatory simulations
Situated learning Lave, Brown Problem and
case-based learning Context awareness
Lifelong and informal learning
Vygotsky Mobile
computer-supported collaborative learning (MCSCL)
Collaborative learning Eraut Supporting intentional
and accidental learning episodes
Personal organisation
Learning and teaching support
N/A Support for
administrative duties (e.g. attendance)
2.4.1 Situated learning
Lave and Wenger (1991) came up with the situated leaning paradigm, that the situation in which learning occurs has a great effect on learners. They argue that learning must not be abstract and out of context. Learning is situated and takes place in the context, activity, and culture in which it occurs as a “legitimate peripheral participation” process. However, Lave and Wenger (1991) emphasise social communication and interaction as being significant part of situated learning. Learning should be presented in an authentic setting supporting knowledge exchange between learners (Naismith et al., 2004). Other researchers support the idea of ‘apprenticeship’. Brown et al. (1989) suggest that teachers or instructors should create authentic contexts for students to learn. Moreover, Holzinger et al. (2005) describe situated learning as a blend of constructivistic and cognitivistic methods, where the situation plays a significant part in the learning construction process.
Defining the key characteristics of situated learning can differ between disciplines and technologies (Yusoff et al., 2010). When designing situated learning using the mix reality technology, Yusoff et al. (2010) outline three main elements: Authentic context, authentic activity/task, and users’ collaboration. Lunce (2006), in designing situated learning using simulation, defines four concepts: a specific context that impacts learning must be defined, peer-based interactions and collaboration between students must take place, knowledge is tacit, and tools must be used to accomplish real-time objectives.
Herrington et al. ’s (2000) elements for situated learning using multimedia and online learning are: Authentic contexts and activities, access to expert
performances and the modeling of processes, multiple roles and perspectives, collaborative construction of knowledge, coaching and scaffolding, reflection to enable abstractions to be formed, articulation to enable tacit knowledge to be made explicit, and integrated authentic assessment.
While situated learning has several benefits, we should be aware of the limitations of the claims as discussed by Anderson et al. (1996) who note that pragmatic aspects such as students’ time constraints and logistics of scheduling activities can result in a division of labour, which can mean that not all students gain the same experience and benefit.
In summary there seems to be a general agreement that although the technologies differ, they all agree on the authenticity of both contexts, activities, and collaboration of learners as key principles of situated learning.
Situated learning has a number of strands in which mobile technologies can play an important role: Context- and location- aware learning, inquiry-based learning, and problem-based learning.
It is important that students are immersed in real-world situations in which they will be working, in order to maximise their learning and knowledge of the issues in the real world, helping to make them more proficient and innovative as designers.
2.4.2 Context-aware and location-based learning
Context-aware location-based computing has attracted researchers’ interest in the past decade. It aims to promote a flowing interaction between human
surroundings of the user to provide an understanding of what is currently happening (Naismith et al., 2004). Abowd et al. (1999, p.3) have defined context, as “Context is any information that can be used to characterize the situation of an entity. An entity is a person, place, or object that is considered relevant to the interaction between a user and an application, including the user and applications themselves”. Besides, Brown et al. (2010, p.4) defines context as “…the formal or informal setting in which a situation occurs; it can include many aspects or dimensions, such as location, time (year/month/day), personal and social activity, resources, and goals and task structures of groups and individuals”. The above two definitions of context lead to the same understanding although the latter is clearer and gives a better understanding. Barkhuus and Dey (2003) define three levels of context-aware applications depending on the interactivity with the user.
1. Personalization: the user determines the way the application behaves in a particular situation.
2. Active context-aware: this is an application that changes the content independently, based of the sensor data.
3. Passive context-aware: the application presents the changed context, sensor data, to the user and lets him/her take control of the decision on the application behaviour.
The research into context-aware mobile learning is still growing with the growth of the technology. The advances in sensing technologies give us the ability to create more novel learning environments for learners. Novel systems can detect the learning behaviour of students in an authentic context and provide the appropriate learning activities and material (Chiou et al., 2010).
Many studies have been conducted in this area while many context-aware systems have been developed in different areas. However, context-aware mobile learning has been the focus for museums and tours in providing information based on the person’s location (Park et al., 2007; Reynolds et al., 2010; Chiou et al., 2010; Costabile et al., 2008; Hsu and Liao, 2011).
Chu et al. (2010) developed a location-aware mobile learning system for a natural science course for primary students. The system uses RFID tags on plants as the sensing technology. This system guides students to a particular plant in order to ask questions and compare similar plants. They argue that the system promotes students’ interest in natural science and improves their learning and achievements. Since we are interested in location- and context- based mobile learning, Chu et al.’s (2010) findings seem to be interesting and provide an example of evaluation. However, results of studies designed as experiments that divides students into two groups, experiment and control groups, should be treated with caution. It should not be applied when the activity is being assessed due to the fact that students in the control group do not have the same opportunity as the experimental group. Thus, it is unfair that their work be assessed equally.
2.4.3 Inquiry-based learning and Problem based learning
In inquiry-based learning, students are given problems that are similar to real world problems to explore, observe, investigate and solve (Feletti, 1993; Shih et al., 2010). Inquiry-based learning is known for the social interaction between learners and their ownership and self-regulation of the learning (Lim, 2004). In Problem-based learning (PBL), students are challenged with
ill-thinking skills (Boud and Feletti, 1997). Main characteristics of PBL are that: (1) students work in a collaborative group, (2) teachers are "facilitators" of learning, (3) the problems do not assess the skill; but help develop it, (4) the performance is assessed, (5) the problem is ill-defined; students gather data, observe the problem and find a solution (Stepian and Gallagher, 1993). Students are encouraged to identify what they already know, the area of knowledge they need to know, and plans on how to solve the problem (Naismith et al., 2004).
Since a real world situation is an important factor in both inquiry-based and PBL, mobile technologies can play an important role in giving students the support they need. Shih et al. (2010) developed a mobile learning activity to guide primary students’ learning in a historic site for a social science course. They claim that students’ achievements’ have risen by 10% and students were enthusiastic as 90.6% strongly agree that using the PDA as a guide is more interesting. Also, they claim that the system helped in lowering the cognitive load of students with low achievements but no significant change was shown with middle and high achieving students. However, Shih et al. (2010) believe that the system can be extended to other courses and other aspects of learning such as critical thinking. Many university courses require students to go investigate real world situations to obtain a better understanding of how things are in reality. These activities might demand evaluation and critical thinking. Therefore, it is interesting to investigate a mobile learning activity that promotes critical thinking in HE students. This gave the idea of investigating to what extent a situated learning activity
assisted by a mobile device can trigger critical thinking and evaluation in HE students.
2.4.4 Collaborative learning
There was a move towards social and collaborative learning back in the early 90s most closely connected to Vygotsky’s (1980) socio-cultural psychology (O’Malley et al, 2003). Pask (1976) produced the conversation theory, in which learning happens when conversations occur between systems of knowledge. These systems could be humans or interactive technologies. In both theories, mobile technologies contribute effectively to promote collaboration and communication (Naismith et al., 2004). Social interaction and discussions with peers lead to group members changing their understanding or constructing new knowledge which results in improving the higher order thinking skills (HOTS) (Ma, 2009). Mobile learning, as a collaborative learning tool, has been under research to prove that it can enrich interactions between students. Much of the computer-supported collaborative (CSCL) learning can be applied to the mobile-supported collaborative learning (MSCL). With the fast emergence of smartphones and mobile applications, students can easily setup group chats and discussions, exchange images, videos and clips through many of the mobile applications in the market, all of which enhance collaborative learning. Many researchers have investigated the use of technology to enhance their students’ collaborative learning. Ma (2009) conducted a study to understand the effect of CSCL in fostering the high order thinking skills. It was concluded that there was a positive relation between quality of the social interaction and the development of HOTS.
course for first year students to collaborate and learn from one another. They found that each student, on average, wrote 34 posts, where the most used feature was commenting. This shows that Facebook has provided a lively medium for students to communicate with each other and with the lecturer. Other researchers have come to the same conclusion, that using Web 2.0 tools encourages and fosters collaboration and sharing (Halic et al., 2010; PIFARRÉ at al., 2013; Leelathakul and Chaipah, 2013).
2.4.5 Lifelong and Informal learning
Informal learning is not a new term. It has been around for a while since Dewey described any learning that happens outside the school as ‘informal learning’ (Dewey, 1997). Informal learning could either happen intentionally or accidentally. This can occur intentionally, through prepared projects (Tough, 1971), or accidentally, through reading a paper, talking to someone, or even watching TV (Eraut, 2000). Studies have shown that most adults learning informally without recognising the process (Tough, 1971). However, the focus on informal learning and the discussions concerning it arose when e-learning came into context. Error! Reference source not found. gives examples of formal and informal learning with regards to planning a learning activity.
Table 2 Types of Formal and Informal Learning (So et al., 2008)
Out of Class Intended learning out of Class
Field trip to a museum which is part of the curriculum
Unintended learning out of Class
Using mobile phones to
capture photographs
and video clips of animal behaviors in a zoo and share them with friends, driven by self-interest
In Class Intended learning in class Reading digital textbooks on a Tablet PC Unintended learning in class Teachable moments,
not planned by teachers
Intended Unintended
Rohs (2008) carried out a study on experts in the field of informal learning, learning, and higher education, to elicit criteria that helps to define informal e-learning.
According to Rohs (2008) an e-learning is defined informal if:
1. The learning environment is technological, non pedagogic, and situated.
2. The learning is self-motivated, self-regulated, and collaborative.
3. The learning has no time limit, it can occur in an anytime anywhere manner.
Cook et al. (2008) argue that informal learning can be linked to formal learning, they state that ‘…being part of a continuum or a multi-dimensional clustering of informal and formal learning activities rather than positioned in an either-or relationship’ (p.4). They suggest that mobile devices can bridge the gap between formal and informal learning.
Therefore, this research can be regarded as having elements from both formal and informal learning, which can be bridged via the use of the mobile smartphone.
2.5 HCI Teaching
Human-computer Interaction studies the way people interact with computers in a particular context and evaluates the extent to which these computer-based systems are, or are not, designed for successful interaction (Benyon, 2010).
Students taking HCI modules usually learn about the role of the task and the context for which the interface will be used, the various interface design constraints and trade-offs and the way the human-computer interaction is affected, as well as the relationship between the interaction and the context of use. They are required to know the potential users of the systems and their goals in order to create a system that is effective, efficient, and intuitive. In addition, they learn about user-centred design methods that require the involvement of the user in the whole process of the system development cycle. This deep understanding of the needs and requirements of the users leads to iterative prototyping and evaluation (Strong et al., 1994). According to McDonagh and Thomas (2010) applying empathic design strategies when designing aids in developing a product that pleases the user. Thus, immersing students into real would environments to gather requirements could generate empathy and thus designing a product that related to the users’ needs.
To facilitate this, the PACT (People, Activities, Context, and Technology) framework is sometimes used to prompt students to consider specific categories in their analysis. The elements of the framework are described by Benyon (2010):
1. People: they differ physically, psychologically, and in terms of their knowledge of technology.
2. Activities: they differ in terms of temporal aspects (response time, frequency of the activity, time pressure and peaks), cooperation, complexity, and safety-criticality.
3. Contexts: the different environments in which the activities take place encompass the organisational and social context and the physical environment.
4. Technologies: these should reflect the specific issues identified in considering the previous elements. Features include input, output, communication, and content.
However, it should be noted that teaching interaction design is a challenging task (Sas and Dix, 2007). Starting from the design process in providing the students with a specific problem and communicating the appropriate feedback (Sas and Dix, 2007). It is highly significant to bridge the gap between theory and practice (Churchill et al., 2013). Thus, immersing students into real world environment is a crucial part of HCI teaching as discussed earlier. Nevertheless, the challenge occurs in the providing students with the problem specification. It is significant that a balance between the level of detail and a room for exploration is achieved (Sas and Dix, 2007). This is a challenge that is acknowledged by the educators. According to Edwards et al. (2006) students studying HCI are usually computer science students who are in favor of clear right or wrong answers and tend to struggle handling less structured tasks which is the nature of HCI (Edwards et al., 2006; Sas and Dix, 2007). Hence educators are constantly trying to identify new approaches to teaching
HCI through exploring the use of technologies in teaching as discussed below.
2.5.1 Uses of technology in HCI teaching
HCI lecturers have been using technology in teaching, or e-learning, for more than a decade. Whether they have used Virtual Learning Environments (VLEs) (Chalk, 2002; Debevc et al., 2008), Wiki-Webs (Brereton et al., 2003), blogging (MacColl et al., 2005), web lectures (Day and Foley, 2006), ePortfolios (Kabicher et al., 2008) or MOOCs (Dix, 2012; Klemmer, 2014). Wang and Karlström (2012) provided undergraduate Interaction Design (ID) students with iPads that have six productivity apps and six design apps preinstalled. It was intended to aid them in their learning activities. The researchers’ aim was to understand the affordances of tablets in the ID learning context. Students, in groups of four, were required to submit a graphic design task every week for the duration of four weeks. Wang and Karlström (2012) found that the iPad had promoted informal learning activities, daily activities such as sending emails, personal use, collaboration, and multimodal interaction. Above all, they argue that collecting data initiated by the student and interacting with the environment was more important than the usage of the context-aware technology. Although this study has shown positive results in using iPads for ID students, some students were concerned about theft and felt uncomfortable taking the iPads in public places such as the subway. This could be an issue when it comes to deploying iPads to aid students’ learning outside the classroom. Not all students own a tablet and borrowing a tablet from the university to be used in public places may put extra pressure on students having to worry about keeping it safe.
As mentioned earlier, previous research into the use of mobile devices and apps have focused on in-class learning. Hence, exploring the effectiveness of mobile location-based apps in aiding students’ understanding of context for design is at the centre of this thesis.
2.6 Critical Thinking and Reflection
Many teachers and lecturers are keen to improve critical thinking skills of their students rather than putting all their effort into delivering content only. However, some promote these skills through teaching the content while others do it explicitly (Fisher, 2001).
2.6.1 Definition
The question that arises now is, what is critical thinking? There are several definitions for critical thinking; some of which are from they early days of Dewey (1933). However, Dewey did refer to his definition as a definition of ‘reflection’, and this will be discussed in a later section.
A popular definition that has been used widely is by Robert Ennis; he stated that critical thinking is "…reasonable, reflective thinking that is focused on deciding what to believe or what to do" (Ennis, 1993, p.180).
Another definition was by Scriven and Paul (1987); they defined it in more detail as "…the intellectually disciplined process of actively and skillfully conceptualizing, applying, analyzing, synthesizing, and/or evaluating information gathered from, or generated by, observation, experience, reflection, reasoning, or communication, as a guide to belief and action". This
definition shows a clear relation to Bloom’s taxonomy, as it relates critical thinking to the three upper levels of the taxonomy: analysis, synthesis, and evaluation(Duron et al., 2006).
The two definitions above agree that a decision and an action need to be made. This shows that critical thinking leads to decision making.
2.6.2 Critical thinking skills
According to Fisher (2001, p.8) there are a number of skills that create critical thinking. To become a critical thinker a person must learn to:
• “Identify elements in a reasoned case, especially reasons and conclusions.
• Identify and evaluate assumptions.
• Clarify and interpret expressions and ideas.
• Judge the acceptability and credibility of claims. • Evaluate different arguments.
• Analyse, evaluate, and produce explanations.
• Analyse, evaluate, and make decisions. • Draw inferences.
• Produce arguments.”
2.6.3 Reflection
Reflection is an every day activity done by people either consciously or subconsciously. According to Moon (2001) people normally reflect on something in order to have a better understanding of it, and usually there is a purpose for this reflection.
